Some researchers [1]} used FCN with CRFs as a post-processing step, but it is computationally expensive.
Consequently, embedding the post-processing steps within a network [2]}, [3]} was a viable solution.
In contrast, we improve the hourglass (encoder-decoder) models without the need to use post-processing steps by introducing additional tasks that refine the latent space.
